Astrocyte transcriptomic changes along the spatiotemporal progression of Alzheimer’s disease

In the paper

“resulting in over 100,000 astrocyte nuclei in each brain region with ≈6,000 average total number of reads and ≈2,500 average total number of genes detected, which is orders of magnitude higher than previous studies9–15”

What the sources say

• Partly supported

  The citing sentence uses Mathys et al. as a previous study for comparison, not as the source of its own dataset’s figures. In “Single-nucleus RNA-seq profiling of prefrontal cortex in human subjects with AD pathology” (page unavailable), Mathys et al. report 80,660 nuclei in total, so their study provides a smaller dataset for comparison. Our copy does not establish the claimed orders-of-magnitude comparison for astrocyte counts, reads, or genes detected. (LLM, conf=0.79)

  cites [9] Mathys, H. et al. Single-cell transcriptomic analysis of Alzheimer’s disease. Nature 570, 332–337 (2019). sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites [10] Grubman, A. et al. A single-cell atlas of entorhinal cortex from individuals with Alzheimer’s disease reveals cell-type-specific gene expression regulation. Nat. Neurosci. 22, 2087–2097 (2019). source
• Disputed

  Extended Data Fig. 7 reports 9,019 astrocyte nuclei out of 66,311 total human nuclei, contrary to over 100,000 astrocyte nuclei in each brain region. The Online Methods report median UMIs and genes per nucleus, not the claimed average reads and genes. (LLM, conf=0.90)

  Checked by a reasoning model — may be wrong.

  cites [11] Zhou, Y. et al. Human and mouse single-nucleus transcriptomics reveal TREM2-dependent and TREM2-independent cellular responses in Alzheimer’s disease. Nat. Med. 26, 131–142 (2020). sourceExperimental — accuracy not yet measured
• Disputed

  The Results (page unavailable) report 42,528 nuclei from the entorhinal cortex and 63,608 from the superior frontal gyrus in total—not over 100,000 astrocyte nuclei in each region. The same passage describes transcript coverage as similar or superior to earlier AD datasets, not orders of magnitude higher; it does not establish the quoted read and gene averages. (LLM, conf=0.90)

  Checked by a reasoning model — may be wrong.

  cites [12] Leng, K. et al. Molecular characterization of selectively vulnerable neurons in Alzheimer’s disease. Nat. Neurosci. 24, 276–287 (2021). sourceExperimental — accuracy not yet measured
• Disputed

  In Results, “Single-Nucleus Transcriptome Profiling of the Prefrontal Cortex in AD” (page unavailable), the paper reports 169,496 nuclei in total from prefrontal cortex samples, with astrocytes comprising 11.9% of those nuclei—not over 100,000 astrocyte nuclei in each brain region. It also says the mean numbers of transcripts and genes detected per nucleus were comparable to a previous study, contrary to the claimed orders-of-magnitude increase. The quoted averages of approximately 6,000 reads and 2,500 genes are not established by these passages. (LLM, conf=0.90)

  Checked by a reasoning model — may be wrong.

  cites [13] Lau, S. F., Cao, H., Fu, A. K. Y. & Ip, N. Y. Single-nucleus transcriptome analysis reveals dysregulation of angiogenic endothelial cells and neuroprotective glia in Alzheimer’s disease. Proc. Natl Acad. Sci. USA 117, 25800–25809 (2020). sourceExperimental — accuracy not yet measured
• Partly supported

  The Results section reports that Sadick et al. captured 41,340 astrocyte nuclei across their final donor cohort, supporting its use as a comparison with a larger dataset. It does not establish that more than 100,000 nuclei per brain region is orders of magnitude higher than its dataset. The STAR METHODS section gives median counts and detected features for all nuclei, not the citing sentence’s average reads and genes for astrocytes. (LLM, conf=0.86)

  cites [14] Sadick, J. S. et al. Astrocytes and oligodendrocytes undergo subtype-specific transcriptional changes in Alzheimer’s disease. Neuron 110, 1788–1805 (2022). sourceExperimental — accuracy not yet measured
• Disputed

  The Introduction and Results (page numbers not provided) report 52,706 astrocyte nuclei in total, not over 100,000 in each brain region. The Results give averages of 8,775 UMIs and 3,166 distinct genes per astrocyte nucleus, rather than the claimed approximately 6,000 reads and 2,500 genes. (LLM, conf=0.90)

  Checked by a reasoning model — may be wrong.

  cites [15] Smith, A. M. et al. Diverse human astrocyte and microglial transcriptional responses to Alzheimer’s pathology. Acta Neuropathol. 143, 75–91 (2022). sourceExperimental — accuracy not yet measured

In the paper

“Because astrocyte morphology changes near Aβ plaques and pTau NFTs23,24”

What the sources say

• Partly supported

  The Spatial Relationships section (page unavailable) reports increased density of reactive astrocytes near dense-core plaques and NFTs. It does not report a change in astrocyte morphology near those lesions; the measured change was in reactive-cell density. (LLM, conf=0.86)

  cites [23] Serrano-Pozo, A. et al. Reactive glia not only associates with plaques but also parallels tangles in Alzheimer’s disease. Am. J. Pathol. 179, 1373–1384 (2011). sourceExperimental — accuracy not yet measured
• Supported

  In “Reactive Astrocytes Associate With Alzheimer’s Pathological Hallmarks” (page not supplied), the paper describes astrocyte processes surrounding and penetrating amyloid plaques and extracellular NFTs. The same section identifies NFTs as containing aberrantly hyperphosphorylated tau, supporting the paraphrase about morphological changes near Aβ plaques and pTau NFTs. (LLM, conf=0.88)

  cites [24] Perez-Nievas, B. G. & Serrano-Pozo, A. Deciphering the astrocyte reaction in Alzheimer’s disease. Front Aging Neurosci. 10, 114 (2018). source

In the paper

“we rank ordered the five brain regions based on their known vulnerability to neurofibrillary degeneration20,21 (that is, EC > ITG > PFC > V2 > V1)”

What the sources say

• ?Not checked — no full text of the sourcecites [20] Braak, H. & Braak, E. Neuropathological staging of Alzheimer-related changes. Acta Neuropathol. 82, 239–259 (1991). source
• Supported

  The staging-system passages describe entorhinal involvement at stage II, spread into temporal neocortex at stages III–IV, and involvement of frontal association cortex at stage V. The stage V–VI passage places secondary visual areas later in the progression and the primary visual (striate) area last. Although the paper does not print the five-region ranking in these abbreviations, its reported progression supports the ordering. (LLM, conf=0.84)

  cites [21] Braak, H., Alafuzoff, I., Arzberger, T., Kretzschmar, H. & Del Tredici, K. Staging of Alzheimer disease-associated neurofibrillary pathology using paraffin sections and immunocytochemistry. Acta Neuropathol. 112, 389–404 (2006). source

In the paper

“the emerging view from experimental data is that reactive astrogliosis may contribute to neurodegeneration through both gains of toxic functions and loss of normal functions1.”

What the sources say

• Supported

  In “Impact in CNS diseases > From morphology to functional studies” (page not supplied), the paper says reactive astrocytes may lose homeostatic functions and gain detrimental functions, exacerbating pathology. The same section gives examples in neurodegenerative disease models, including lost functions in Huntington’s and Alzheimer’s disease and a potentially detrimental gain of function in Alzheimer’s and Parkinson’s disease. (LLM, conf=0.93)

  cites [1] Escartin, C. et al. Reactive astrocyte nomenclature, definitions, and future directions. Nat. Neurosci. 24, 312–325 (2021). source

In the paper

“Previous transcriptomic studies comparing AD mouse models have reported similarities and differences in astrocyte responses to Aβ plaques versus pTau NFTs5,7,33.”

What the sources say

• Supported

  The Introduction says the study compares astrocyte responses to Aβ and Tau pathology in mouse models to identify common effects and differences. The Results report a core set of genes induced in both models, while the Discussion notes genes induced in only one model. The copy provides no page numbers for these passages. (LLM, conf=0.92)

  cites [5] Jiwaji, Z. et al. Reactive astrocytes acquire neuroprotective as well as deleterious signatures in response to Tau and Aβ pathology. Nat. Commun. 13, 135 (2022). source
• Supported

  The section “Induction of Brain Complement Expression in PS2APP and TauP301S Mice” (page unavailable) compares gene-expression profiles in astrocytes from amyloidosis and tauopathy mouse models. Both showed increased classical complement gene expression, while TauP301S astrocytes showed stronger reactive-gene induction than PS2APP astrocytes. This supports the claimed similarities and differences. (LLM, conf=0.92)

  cites [7] Wu, T. et al. Complement C3 is activated in human AD brain and is required for neurodegeneration in mouse models of amyloidosis and tauopathy. Cell Rep. 28, 2111–2123 (2019). source
• Partly supported

  The Introduction and results describe a transcriptomic comparison of hippocampal GFAP-positive astrocytes from PS2APP amyloidosis and Tau P301S mouse models, finding a small overlap of differentially expressed genes and distinct responses. The Discussion also reports inflammation-related changes in both models. The paper frames the comparison as Aβ versus tau pathology; the cited passages do not establish responses specifically to Aβ plaques versus phosphorylated-tau neurofibrillary tangles. (LLM, conf=0.82)

  cites [33] De Bastiani, M. A. et al. Hippocampal GFAP-positive astrocyte responses to amyloid and tau pathologies. Brain Behav. Immun. 110, 175–184 (2023). sourceExperimental — accuracy not yet measured

In the paper

“by definition, the primary visual cortex (V1 region) bears NFTs only in Braak NFT stage VI20,21”

What the sources say

• ?Not checked — no full text of the sourcecites [20] Braak, H. & Braak, E. Neuropathological staging of Alzheimer-related changes. Acta Neuropathol. 82, 239–259 (1991). source
• Supported

  The staging-system section (Major characteristics of stages V–VI; page unavailable) identifies involvement of the striate area, or V1, as a key feature of stage VI. It notes isolated neuritic plaques and AT8-immunoreactive neurons there at stage V, but does not identify these as NFTs; the Fig. 5 caption describes the striate area as uninvolved at that stage. (LLM, conf=0.84)

  cites [21] Braak, H., Alafuzoff, I., Arzberger, T., Kretzschmar, H. & Del Tredici, K. Staging of Alzheimer disease-associated neurofibrillary pathology using paraffin sections and immunocytochemistry. Acta Neuropathol. 112, 389–404 (2006). source

In the paper

“Astrocytes are critical for maintaining brain homeostasis2”

What the sources say

• Supported

  The paper’s “Definition and Overview of Function” section says astrocytes sustain and control CNS homeostasis at levels from molecules to the whole organ. It also describes their homeostatic functions as vital to CNS operation, supporting the claim that they are critical for maintaining brain homeostasis. (LLM, conf=0.94)

  cites [2] Verkhratsky, A. & Nedergaard, M. Physiology of astroglia. Physiol. Rev. 98, 239–389 (2018). source

In the paper

“These AD neuropathological changes (ADNC) are accompanied by a dramatic loss of synapses and neurons, as well as prominent morphological and functional changes of glial cells, collectively termed reactive gliosis1.”

What the sources say

• Partly supported

  The paper’s “Morphology revisited” section describes changes in astrocyte branches in AD mouse models, and “From morphology to functional studies” describes altered reactive-astrocyte functions in AD models. Its discussion of gliosis also supports the general terminology. The cited passages do not establish the claimed dramatic loss of synapses and neurons accompanying AD neuropathological changes; pages are not available in our copy. (LLM, conf=0.86)

  cites [1] Escartin, C. et al. Reactive astrocyte nomenclature, definitions, and future directions. Nat. Neurosci. 24, 312–325 (2021). sourceExperimental — accuracy not yet measured

In the paper

“Although all but one study10 had astTinf, only the largest study—the Seattle Alzheimer’s Disease Brain Cell Atlas (SEA-AD)17, performed in the middle temporal gyrus—had a sizable representation of the exhausted astMet subcluster.”

What the sources say

• ?Not checked — no full text of the sourcecites [10] Grubman, A. et al. A single-cell atlas of entorhinal cortex from individuals with Alzheimer’s disease reveals cell-type-specific gene expression regulation. Nat. Neurosci. 22, 2087–2097 (2019). source
• Partly supported

  The Results section identifies SEA-AD as an MTG atlas, and Fig. 4b depicts it as larger than the publicly available datasets. But the copy does not identify astTinf or astMet, or establish that only SEA-AD had a sizable astMet subcluster (searched: astTinf, astMet, exhausted astrocyte subcluster). (LLM, conf=0.83)

  cites [17] Gabitto, M. I. et al. Integrated multimodal cell atlas of Alzheimeras disease. Nat. Neuro. https://doi.org/10.1038/s41593-024-01774-5 (2024). sourceExperimental — accuracy not yet measured

In the paper

“previous bulk transcriptomic analyses have highlighted energy metabolism deficits as a feature of AD and other neurodegenerative diseases43,44”

What the sources say

• Supported

  The Discussion reports that a meta-analysis of bulk microarray transcriptomic datasets from AD, LBD, and ALS-FTD found downregulation of genes involved in mitochondrial electron transport and energy metabolism. It also identifies failure of neuronal energy metabolism as a shared feature of these diseases. (LLM, conf=0.94)

  cites [43] Noori, A., Mezlini, A. M., Hyman, B. T., Serrano-Pozo, A. & Das, S. Systematic review and meta-analysis of human transcriptomics reveals neuroinflammation, deficient energy metabolism, and proteostasis failure across neurodegeneration. Neurobiol. Dis. 149, 105225 (2021). source
• Supported

  The Abstract describes a meta-analysis of human CNS transcriptomic datasets spanning AD and other neurodegenerative diseases. The Specifications Table identifies the related research article as a transcriptomic meta-analysis that found deficient energy metabolism across neurodegeneration (page not provided). (LLM, conf=0.84)

  cites [44] Noori, A., Mezlini, A. M., Hyman, B. T., Serrano-Pozo, A. & Das, S. Differential gene expression data from the human central nervous system across Alzheimer’s disease, Lewy body diseases, and the amyotrophic lateral sclerosis and frontotemporal dementia spectrum. Data Brief. 35, 106863 (2021). source

In the paper

“astrocytes have been reported to contribute to the (18F)fluoro-deoxy-glucose (FDG)–positron emission tomography (PET) signal via the glutamate transporter EAAT2/GLT-1, encoded by SLC1A2 (ref. 45)”

What the sources say

• Partly supported

  The paper’s Abstract (page unavailable) reports that astrocytic glutamate transport via GLT-1 contributes to the [18F]FDG PET signal. Our copy does not identify GLT-1 as EAAT2 or state that it is encoded by SLC1A2, so those identifiers are not supported by this source. (LLM, conf=0.84)

  cites [45] Zimmer, E. R. et al. [18F]FDG PET signal is driven by astroglial glutamate transport. Nat. Neurosci. 20, 393–395 (2017). sourceExperimental — accuracy not yet measured

In the paper

“higher plasma GFAP levels have been associated with higher (18F)FDG–PET signals in early AD46”

What the sources say

• Supported

  The Discussion identifies a positive association between plasma GFAP and cerebral glucose consumption early in the Alzheimer’s continuum. The Correlations with cerebral [18F]FDG uptake section reports a positive correlation with PET uptake; the Discussion notes that the association can turn negative in some regions among tau-positive individuals. (LLM, conf=0.93)

  cites [46] Salvadó, G. et al. Reactive astrogliosis is associated with higher cerebral glucose consumption in the early Alzheimer’s continuum. Eur. J. Nucl. Med. Mol. Imaging 49, 4567–4579 (2022). source

In the paper

“RORB had previously been identified by snRNA-seq as a marker gene for excitatory EC neurons that are vulnerable to NFTs and neurodegeneration in AD12”

What the sources say

• Supported

  The Introduction (page not provided) says the authors used snRNA-seq to discover a selectively vulnerable excitatory-neuron subpopulation in the entorhinal cortex. The Results (page not provided) identify RORB as a marker of vulnerable EC excitatory-neuron subpopulations and report both their depletion during AD progression and preferential phospho-tau accumulation. (LLM, conf=0.94)

  cites [12] Leng, K. et al. Molecular characterization of selectively vulnerable neurons in Alzheimer’s disease. Nat. Neurosci. 24, 276–287 (2021). source

In the paper

“the distinguishing feature between Braak NFT stages V and VI is not just the presence of NFTs in the primary visual (V1), motor and sensory cortical areas, but more severe neurofibrillary degeneration21 and atrophy throughout the cortical mantle51”

What the sources say

• Supported

  In “Major characteristics of stages V–VI” (page not provided), the paper describes stage VI as reaching primary neocortical areas, including the striate area, and reports severe pathology across most of the neocortex, compared with more limited involvement at stage V. This supports the neurofibrillary-degeneration distinction attributed to this source. The sentence cites a different source for cortical atrophy, so that portion is not assessed here. (LLM, conf=0.89)

  cites [21] Braak, H., Alafuzoff, I., Arzberger, T., Kretzschmar, H. & Del Tredici, K. Staging of Alzheimer disease-associated neurofibrillary pathology using paraffin sections and immunocytochemistry. Acta Neuropathol. 112, 389–404 (2006). source
• Partly supported

  The Results report cortical atrophy in patients with early-stage Alzheimer’s disease, and the Discussion reports an association between global cortical tau-PET signal and global cortical atrophy (pages unavailable). The paper does not compare Braak NFT stages V and VI or establish that more severe atrophy throughout the cortical mantle distinguishes them. Citation 51 is attached to the atrophy portion of the sentence, not the separate claim about neurofibrillary degeneration. (LLM, conf=0.79)

  cites [51] La Joie, R. et al. Prospective longitudinal atrophy in Alzheimer’s disease correlates with the intensity and topography of baseline tau-PET. Sci. Transl. Med. 12, eaau5732 (2020). sourceExperimental — accuracy not yet measured

In the paper

“our sample sizes are similar to those reported in previous publications9–17”

What the sources say

• Supported

  The Methods section, “Selection of individuals from the Religious Order Study (ROS) cohort” (page not provided), reports a sample of 48 individuals: 24 controls and 24 with AD pathology. This supports the citation as an example of a previous publication reporting a sample size; the comparison with the citing study’s own sample size is the citing authors’ assessment. (LLM, conf=0.90)

  cites [9] Mathys, H. et al. Single-cell transcriptomic analysis of Alzheimer’s disease. Nature 570, 332–337 (2019). source
• ?Not checked — no full text of the sourcecites [10] Grubman, A. et al. A single-cell atlas of entorhinal cortex from individuals with Alzheimer’s disease reveals cell-type-specific gene expression regulation. Nat. Neurosci. 22, 2087–2097 (2019). source
• Supported

  The Online Methods (‘Mice’; page not provided) report three male mice per genotype for snRNA-seq and give sample sizes for other assays. The paper therefore supplies the prior-study sample sizes cited; whether the citing authors’ own sample sizes are similar is their comparison, not a finding attributed to this source. (LLM, conf=0.85)

  cites [11] Zhou, Y. et al. Human and mouse single-nucleus transcriptomics reveal TREM2-dependent and TREM2-independent cellular responses in Alzheimer’s disease. Nat. Med. 26, 131–142 (2020). source
• Supported

  The Sample sizes passage (labelled Discussion in our copy; page not provided) explicitly says the authors’ sample sizes were comparable to those in previous publications. This directly supports the paraphrase. (LLM, conf=0.94)

  cites [12] Leng, K. et al. Molecular characterization of selectively vulnerable neurons in Alzheimer’s disease. Nat. Neurosci. 24, 276–287 (2021). source
• Supported

  The Results section, “Single-Nucleus Transcriptome Profiling of the Prefrontal Cortex in AD” (page unavailable), reports sample sizes of 12 AD and 9 control subjects. The citation identifies a previous publication that reports sample sizes; the comparison with the citing study’s own sizes is the citing authors’ assessment. (LLM, conf=0.88)

  cites [13] Lau, S. F., Cao, H., Fu, A. K. Y. & Ip, N. Y. Single-nucleus transcriptome analysis reveals dysregulation of angiogenic endothelial cells and neuroprotective glia in Alzheimer’s disease. Proc. Natl Acad. Sci. USA 117, 25800–25809 (2020). source
• Supported

  In STAR METHODS, under “Quantification and Statistical Analysis—Sample size estimation,” the paper explicitly says its donor cohort is similar in size to those in published works by Grubman et al. and Leng et al. This supports the cited comparison of sample sizes. (LLM, conf=0.94)

  cites [14] Sadick, J. S. et al. Astrocytes and oligodendrocytes undergo subtype-specific transcriptional changes in Alzheimer’s disease. Neuron 110, 1788–1805 (2022). source
• Supported

  The Methods (Brain tissue; page not available) report 6 control and 6 Alzheimer’s disease cases, yielding 24 brain samples. This supports citing Smith et al. as a previous publication with a reported sample size; the comparison with the citing authors’ own sample size is their framing, not a finding attributed to Smith et al. (LLM, conf=0.85)

  cites [15] Smith, A. M. et al. Diverse human astrocyte and microglial transcriptional responses to Alzheimer’s pathology. Acta Neuropathol. 143, 75–91 (2022). source
• Supported

  The Discussion reports 11,337 astrocyte nuclei across 15 samples, and the Results report validation data from 10 normal and 10 Alzheimer’s disease brains. This source therefore supplies sample sizes from a previous publication; whether they are similar to the citing study’s sizes is the citing authors’ comparison, not a finding attributed to this source. (LLM, conf=0.85)

  cites [16] Dai, D. L., Li, M. & Lee, E. B. Human Alzheimer’s disease reactive astrocytes exhibit a loss of homeostastic gene expression. Acta Neuropathol. Commun. 11, 127 (2023). source
• Supported

  The Methods section (‘Statistics, data visualization and reproducibility’) explicitly states that the study’s sample sizes are similar to those reported in previous publications. The difference in reference numbers does not change the attributed claim. (LLM, conf=0.95)

  cites [17] Gabitto, M. I. et al. Integrated multimodal cell atlas of Alzheimeras disease. Nat. Neuro. https://doi.org/10.1038/s41593-024-01774-5 (2024). source

In the paper

“Interestingly, the gene set decreasing linearly from EC to V1 (gene set 1) was positively correlated with the pTau/tau ratio, whereas the one increasing from EC to V1 (gene set 2) was negatively correlated with the pTau/tau ratio”

In the paper

“The last two spatial gene sets exhibited relatively constant expression levels in EC, ITG and PFC, but either decreased (gene set 5) or increased (gene set 6) from the PFC to V2 and V1.”

In the paper

“Conversely, CLU, GFAP and MAOB were upregulated, whereas AQP4 and GJA1 were downregulated in V1 versus all other brain regions.”

In the paper

“Among other genes of interest, APOE, APP, AQP4 and GJA1 were upregulated, whereas ALDH1L1, LRP1B, microtubule-associated protein tau (MAPT) and SLC1A2 were downregulated in EC relative to the other brain regions.”

In the paper

“Only 18 of the 137 EC-upregulated genes were positively correlated with the pTau/tau ratio (notably including cytoskeletal genes such as MAP2 and the master transcription factor regulating cholesterol metabolism, SREBF1), whereas only 37 of 152 EC-downregulated genes were negatively correlated with the pTau/tau ratio (including extracellular matrix/glycosaminoglycan metabolism genes, such as LARGE”

In the paper

“Our eight control donors provided a unique opportunity to examine regional differences in the astrocyte transcriptome in the normal aging brain because these donors had essentially no 3D6-positive Aβ plaques across the five brain regions and very low pTau/tau ratios except for the EC”

In the paper

“Two spatial gene sets changed their expression level monotonically along the network, either decreasing from EC to V1 (gene set 1) or increasing from EC to V1 (gene set 2).”

In the paper

“By contrast, the pTau/tau ratio was highest in EC and demonstrated the expected pattern EC > ITG > PFC > V2 > V1 across all stages”

In the paper

“This gene set was enriched in synapse-associated (DISC1, GRIA4, GRID2 and SYNDIG1), cell–cell communication (APBB1IP, EFNA5, EPHA6 and SPP1) and cytoskeletal (SYNM and FMN1) genes that were distinct from those associated with the pTau/tau ratio (Fig. 3c).”

In the paper

“The upregulated late gene program comprised genes involved in proteostasis/response to heat stress (AHSA1, BAG3, CCT4, CRYAB, DNAJA1, DNAJB1, DNAJB6, HSP90AA1, HSP90AB1, HSPA1A, HSPA1B, HSPA4, HSPA4L, HSPA8, HSPA9, HSPB1, HSPD1, HSPE1, HSPH1, MIB1, OTUD7B, SQSTM1, ST13, UBB, UBC, UBE2B and UBE2E2), protein translation (EEF1A1, EIF1, EIF2S2, RPL37A, RPL38, RPLP2, RPS21, RPS24 and RPS28), energy”

In the paper

“Two small clusters had genes typically found in other cell types, specifically neurons (astNeu) and microglia (astMic), and were considered hybrids or doublets (although their estimated doublet score was very low).”

In the paper

“another sizable gene set (gene set 4, n = 120), characterized by its lack of correlation with either Aβ or pTau levels and highest expression levels in the EC and V1, was composed of genes related to the cytoskeleton (including GFAP), lipid metabolism (including APOE and CLU), calcium homeostasis, extracellular matrix, heat-shock proteins and antioxidant defense (for example, metallothioneins)”

In the paper

“These 798 DEGs were grouped into six different temporal gene sets with distinct temporal trajectories and variable strength of association with the local Aβ and pTau levels (Fig. 4 and Supplementary Data 5).”

In the paper

“Finally, gene set 6 had low expression at early and intermediate stages, peaked at the late stage and decreased at the end stage without returning to baseline”

In the paper

“The proportion of homeostatic, intermediate and reactive astrocytes changed only along the spatial axis, whereas two other subclusters changed along the temporal axis.”

In the paper

“This gene set included many trophic factors and their receptors (ANGPTL4, APC, EGLN3, FGF2, GFRA1, HGF, IGF1R, NRP1, NTRK3, TGFB2, TGFBR3 and VEGFA), extracellular matrix (GPC4, MATN2, SERPINA3, SERPINE2 and SPOCK1), cytoskeleton (ACTN1, FIGN, MACF1, MAPRE2, MAST4 and MYH9) and some metal binding (CP, FTL and MT2A), antioxidant (MGST1 and MSRA) but also pro-oxidant enzymes (MAOB), neuroin”

In the paper

“This early gene program included trophic and survival factors (FGF1, FGF14, HIF1A and NRP2), extracellular matrix (GPC6, KAZN, LAMA4 and TNC), cytoskeleton (ABI1, CLIP1, MYO1E and VCL) and neuroinflammation (CHI3L1, IFI16, IL1R1, IL6R and RCAN1) genes, which differ from those predominant in the early ADNC stage. It also encompassed genes involved in lipid metabolism (ACSL3, ELOVL5, ELOVL6, LDLR, L”

In the paper

“While some of the subclusters were associated with age, the effect sizes were very small (β = −0.008 to 0.004).”

In the paper

“a spatial quantitative analysis centered in thioflavin-S-positive dense-core Aβ plaques demonstrated a gradient of expression of the reactive markers from the plaque to the peri-plaque halo (≤50 μm) to areas distant (>50 μm) from plaques in the AD cortex, whereas no effect of sham plaques was observed in control cortex”

In the paper

“only astMet was significantly associated with sex (higher frequency in female donors, P < 0.005), but the effect size was small (β = 0.046).”

In the paper

“While this gene set was negatively correlated with both Aβ plaque burden and pTau/tau ratio, the statistical significance was lost after controlling for brain region.”

In the paper

“confirmed the highest expression in stage 3 and very low expression in stage 4”

In the paper

“the proportion of homeostatic astH0 astrocytes was significantly reduced in EC versus all other regions but did not change with pathology stages”

In the paper

“astR1 and astR2 were enriched in GFAP, S100B, HSF1-mediated stress response (CRYAB, HSPA1B, HSPB8 and UBC), extracellular matrix (CD44, COL21A1, GPC6, LAMA4, SERPINA3, TNC and VCAN) and oxidative stress (MAOB), but differed in some other marker genes”

In the paper

“astMet exhibited a positive enrichment in temporal gene set 3 (characterized by upregulation of proteostasis, mitochondrial electron transport chain and metallothioneins in pathology stage 3 and normalization in pathology stage 4) and a negative enrichment of temporal gene set 4”

In the paper

“the significantly increased frequency of astMet in pathology stage 3 relative to pathology stages 1 and 2, with a subsequent decrease in pathology stage 4”

In the paper

“The gene set with relatively stable expression in EC through PFC and lower expression in V2 and V1 (gene set 5) was enriched in EC-low and V1-low genes, and the gene set with stable levels in EC through PFC but increase in V2 and V1 (gene set 6) was expectedly enriched in V1-high genes (Fig. 3b).”

In the paper

“we identified an EC-specific astrocyte signature, which included changes in genes relevant to AD pathophysiology such as an upregulation of APP and APOE and a downregulation of SLC1A2 (encoding the glutamate transporter EAAT2, a.k.a. GLT-1) and MAPT (encoding the microtubule-associated protein tau) relative to other cortical regions”

In the paper

“Finally, spatial gene set 5 was positively correlated with both pTau/tau ratio and Aβ plaque burden, whereas gene set 6 was negatively correlated with both measures”

In the paper

“both astR1 and astR2 reactive astrocytes were more frequent in EC and ITG, and the frequency of astR1 tended to increase with pathology stages”

In the paper

“The gene set specifically upregulated in PFC (gene set 3) was not enriched in either EC or V1 signatures, whereas the gene set specifically downregulated in PFC was enriched in EC-high and V1-high genes.”

In the paper

“Subcluster astR0 also exhibited a reactive phenotype and was further enriched in extracellular matrix genes (COL21A1, COL24A1, COLGAT and LAMA2).”

In the paper

“Two other temporal gene sets either peaked (gene set 3) or dropped (gene set 4) at the late stage (moderate/frequent NPs, Braak NFT stage V) but surprisingly returned to near baseline at end stage (moderate/frequent NPs, Braak NFT stage VI)”

In the paper

“The proportion of reactive astR0 astrocytes increased in parallel with pathology stages and decreased along brain regions from EC to V1.”

In the paper

“Specifically, the gene set with monotonic decrease from EC to V1 (gene set 1) was significantly enriched in EC-high and V1-low genes, whereas the gene set with monotonic increase from EC to V1 (gene set 2) was significantly enriched in EC-low and V1-high genes.”

In the paper

“the reactive subclusters had a positive enrichment score for spatial gene set 1 (positively correlated with pTau) as well as spatial gene set 4 (stress chaperones/heat-shock response genes) and a negative enrichment score for spatial gene set 2 (negatively correlated with pTau), whereas the homeostatic subcluster astH0 demonstrated the opposite effects”

In the paper

“the frequency of astIM declined along the spatial axis but was reduced only in pathology stage 3”

In the paper

“the homeostatic astH0 astrocytes also transitioned to astMet and astTinf, which appeared to be terminal states with no further progression into the reactive subclusters”

In the paper

“reactive astrocytes represent less than 25% of all astrocyte nuclei and express higher levels of aquaporins, heat-shock proteins, extracellular matrix and cytoskeletal genes”

In the paper

“homeostatic astrocytes constitute the majority of the astrocyte population, regardless of the severity of AD pathology, and express higher levels of typical homeostatic genes such as glutamate metabolism-related genes”

In the paper

“these results could be indicating that astrocytes, as part of the tripartite excitatory synapses, have a key role in synaptic dysfunction and the trans-synaptic propagation of pTau between excitatory neurons along vulnerable AD neural networks”

In the paper

“astMet and astTinf are distinct subclusters that deviate from the prototypical homeostatic-to-reactive transition path”

In the paper

“these data suggest that astMet are undergoing exhaustion, that is, failure in proteostasis and energy metabolism, after prolonged exposure to ADNC (Braak stage VI).”

In the paper

“Our data confirm that astrocytes, in addition to neurons, suffer mitochondrial dysfunction and energy deficits that contribute to these observed bulk RNA changes and could also potentially contribute to clinical progression.”

In the paper

“possibly reflecting differences in the duration of each stage across donors.”

In the paper

“reactive astrocytes may initially increase their metabolic rate but finally fail to meet their energy needs and contribute to the typical bilateral temporoparietal hypometabolism observed in AD”

In the paper

“Together, these results underscore the dynamic, complex and nonlinear pattern of astrocyte transcriptomic changes along AD progression”

In the paper

“These findings indicate that astMet and astTinf are unique terminal subclusters with a complex, stage-dependent response to ADNC”

In the paper

“likely representing ADNC-associated pan-reactive upregulated and downregulated signatures, respectively.”

In the paper

“uncovering two terminal states that are off-pathway the prototypical astrocyte reactivity, including a previously unrecognized exhausted state”

In the paper

“and suggest that these astrocyte transcriptomic changes are partly associated with the local levels of Aβ plaques and/or pTau and partly explained by region-specific microenvironmental factors.”

In the paper

“Data were analyzed running mixed-effects models with diagnosis and location as fixed effects and donor ID as random effect to account for within-donor correlation.”

In the paper

“Batch effects due to technical variation were corrected using the RunHarmony function in Harmony (v.0.1.1) package64, with the top 20 principal components as input.”

In the paper

“in each AD donor, n = 50 Thioflavin-S-positive dense-core plaques were randomly selected and outlined throughout all layers of the cortical ribbon in the green channel being blindfolded to the expression level of the reactive astrocyte marker of interest in the red channel.”

In the paper

“For each brain region, we removed cells with fewer than 200 genes, greater than 20,000 unique molecular identifiers (UMIs) and/or greater than 15% mitochondrial genes”

In the paper

“After filtering, a second round of integration was performed via canonical correlation analysis to regress out donor-specific effects as well as the percentage of mitochondrial genes.”

In the paper

“no randomization was performed”

In the paper

“RIN value was measured from 130 donors, of which 83 met the selected cut-off of RIN ≥ 5.”

In the paper

“Statistical analyses were conducted with mixed-effects models with area fraction of the reactive marker as the dependent variable, diagnosis (control versus AD) and location (sham or Thioflavin-S-positive plaque, ≤50 μm halo, or >50 μm) as fixed effects and controlling for donor ID (random effect).”

In the paper

“corresponds to the exhausted astrocytes whose proportion and gene expression program peak in AD late stage (Braak stage V) and normalize in end stage (Braak stage VI)”

In the paper

“Data collection and analysis were not performed blind to neuropathological diagnosis.”

In the paper

“No donors or samples were excluded from the analysis.”

In the paper

“Astrocyte nuclei were identified by their high expression of ADGRV1, ALDH1L1, AQP4 and GFAP.”

In the paper

“No statistical methods were used to predetermine sample sizes”

In the paper

“Significance was evaluated by a two-sided Welch’s t test. P values were adjusted using the Benjamini–Hochberg method to correct for multiple comparisons when two or more comparisons were conducted within studies.”

In the paper

“Donors were selected based on their global AD neuropathological burden”

In the paper

“used reciprocal principal component analysis (rPCA) integration based on the top 2,000 highly variable genes (HVGs) to remove donor-specific effects using the Seurat R package (v.4.3.0)60.”

In the paper

“Multiplex fluorescence immunohistochemistry images in Figs. 2c and 5d as well as Supplementary Figs. 5, 6 and 7 have the same display settings across brain regions and diagnoses.”

In the paper

“The effects of factors such as age and sex on cell subcluster frequency across samples were modeled using multiple linear regression with the formula: frequency ~1 + pTau/tau + region + sex + age + pTau/tau × sex + pTau/tau × region.”